Fraser River Sockeye Fisheries and Fisheries Management - Cohen ...

The caption of Figure 11 has been corrected.Page 60: Attention is also drawn to the use of linear regressions of total returns versus forecastsfor many stocks. The authors compute coefficients of determination (r 2 ) and use it as a measureof fit to explain the proportion of the variation in total returns explained by the independentvariable (here the forecast). However, there is no reason to assume that the relations are linear. Anon-linear exponential functions would likely provide a better fit to the data for the early Stuartand Early Summer stocks (p. G-3 and G-4), and a quadratic might be more suitable for theBirkenhead stock (p. G-7). These observations suggest that for some stocks, the best forecastingrelations may lack a crucial co-factor that has yet to be identified. Some of the other relations areseemingly linear, but the bi-variate error structure does not always look normal. If so, it would beadvisable to use non-parametric correlation coefficients (Kendall or Spearman’s, see Zar 1984 p.318) (Zar, J.H. 1984. Biostatistical Analysis. Second edition. Prentice-Hall. New Jersey. 718 p.)to crudely gage the functional dependence of one variable on the other, and perhaps use it as an‘indicator of reliability’ for other comparisons in the report.LGL Response: We disagree, there is indeed reason to assume the relationship betweenforecast and return will be linear because the actual return value is exactly what a forecastis meant to match. If the forecast predicts 1M fish, we expect the return to be 1M. If theforecast predicts 1,000 fish, we expect the return to be 1,000. We agree the formulae usedto derive forecast values are not linear and loaded with multiple co-factors (we reviewforecast models elsewhere in the report), but the (lack of) linearity in forecast models isirrelevant to the complaint raised here by the reviewer.We have re-run the regression analyses on log 10 transformed data to improve the bivariatedistribution of data in the regression analyses. In general, R 2 values were lowered whichfurther substantiates our conclusion that pre-season forecasts do not adequately predictactual returns and management decisions should rely instead on in-season test fishing andin-season estimates etc. We have revised figures and text throughout report and appendix.Page 67: The authors note that Bayesian statistical techniques have recently been use to a greaterextent for in-season monitoring. They note that some Bayesian models were formulated by BillGazey, but no references are given to confirm that a peer review was done to support the notionthat this method is superior to others used previously.Pages 72 & 75: It is noted that fishwheels are used to “estimate the near-shore speciescomposition in recent years”. This is actually a recently implemented and very expensive projectconducted by LGL Ltd in the lower Fraser River. A few additional comments seem required toM-19